Intensive Pro.2 | Uncovering data commodification…

Sacrificing Privacy for Global Connection?…

Thoughts over the previous weeks…

  • Creating indistinguishable identities in the oversaturated social network sphere, obscured or blurred identities, loss of identity through repeated or reappropriated visual characteristics.
  • Look at and consider visual cues, similarities and repetitions through social media posts.
  • ‘Professionally Recreating these images?’ Adopting visual cues and characteristics? Data Trails, visualising data spaces and clusters in relation to consumption and lifestyle displays.

Exploring my Ideas Photographically…

Image Traces & Montage:

 

 

Most businesses now have active profiles on Facebook and Twitter, but an Instagram account is also a must. It’s actually now the second-most active of the big three, with over 300 million daily users.”

“Instagram users engage more per post than any other social network. Furthermore, 50 percent of users follow at least one business. This business could be yours!”

“A range of paid advertising options are also available on Instagram for those that want to supplement or bypass organic posting. According to the company’s pitch, 70 percent of performance campaigns have generated statistically significant lifts for advertisers for online conversion or mobile app installs.”

 Connect With Your Niche

“If you want to find your audience on Instagram, you will need to connect with the competition and their followers, influencers and thought leaders, and other profiles related to your industry. This includes following them (in hope they will return the favor) but also commenting, liking and sharing their posts when it’s suitable and you have something of value to add.”

Utilize Hashtags

“On Instagram, using hashtags is one of the primary ways you can attract new targeted followers.”

“The benefit is that when a user searches on Instagram, the results are drawn from these hashtag feeds, i.e. if you used the hashtag #soccer in a recent post and somebody searches “soccer,” they will see your post in the feed even if they don’t follow you. Perhaps now they will? Users might also follow a specific hashtag to get aggregated content on their favorite subjects.”

Marketers need to strike a balance between broad and popular terms, highly relevant terms, and not including too many per posts — which can appear spammy.”

Promoted Posts

“Instagram’s paid advertising options include “promoted posts,” which take your regular posts and put them directly in front of the audience you choose. Options include age, gender, location and interests, so you can really laser target your campaign.”

“There are currently around 500,000 advertisers on the platform, so pricing is still competitive.”

Partnerships

“This might involve giving review copies of products or free access to services, with the agreement that the user promotes them and gives their honest opinion. You can even directly pay users to promote your brand.”

“One of the most liked photos of all time on Instagram, and an example of influencer marketing, is actress and singer Selena Gomez promoting Coca-Cola.”

Credit score – Digital Identity | ‘Datafication’

‘What is My Credit Score, and How is it Calculated?’

 

“While your credit reports are simply a track record of your payment history—no judgments—your credit score is more akin to a school GPA. It’s a cumulative number that measures your success relative to others, in this case grading you as a credit-worthy individual.”

“But credit scores aren’t just used by banks. Increasingly, insurance firms, landlords and even employers are using credit scores as a proxy for figuring out how responsible you are.”

“The most widely used score, from a company called FICO, ranges from 300 to 850. On the FICO scale, the higher the number, the better. In general, anything over 740 is considered excellent and will qualify you for the best rates: if your score is below 650, you’ll pay very high rates on loans and credit cards, if you qualify for them at all.”

“Even 20 or so points can make a big difference in what you’ll pay for credit. Someone with a score of 659 could get a 30-year mortgage at 5.3% at today’s rates; if his score was 680 he’d qualify for a loan at just 4.7%. That’s about $950 a year less in interest, or about $28,000 over the life of the loan.”

“Fair Isaac, the makers of the FICO score, is tight-lipped about exactly how the scores are calculated. But they do give the weights of various criteria that they look at: 35% payment history, 30% amount owed, 15% length of history, 10% new credit, 10% types of credit used.”

“The most important factor in determining your score, payment history, is simply a record of whether you’ve paid your bills on time. The second more important, amount owed, is a little more complicated. It looks at how much you’re using of the total credit you have available – also known as your “utilization ratio.”

“Lenders believe that borrowers who are close to maxing out their credit are more likely to miss payments. The third factor, length of history, is determined by the average age of your accounts, as well as how long it’s been since those accounts were used. The two smallest factors are how often you’ve opened new accounts (opening a bunch at once will hurt your score), and whether you’ve got a mix of different types of credit (such as a mortgage, student loan and car loan). Lenders like to know that you can manage different kinds of accounts responsibly.”

‘What’s in my FICO Scores’

 

“Your FICO Scores consider both positive and negative information in your credit report. Late payments will lower your FICO Scores, but establishing or re-establishing a good track record of making payments on time will raise your score.”

“For some groups, the importance of these categories may vary; for example, people who have not been using credit long will be factored differently than those with a longer credit history.”

“Therefore, it’s impossible to measure the exact impact of a single factor in how your credit score is calculated without looking at your entire report. Even the levels of importance shown in the FICO Scores chart are for the general population, and will be different for different credit profiles.”

“Your credit score is calculated from your credit report. However, lenders look at many things when making a credit decision such as your income, how long you have worked at your present job and the kind of credit you are requesting.”

Corresponding Categories:

‘Experian – Introducing your Data Self’ [Ego- Serfing]

“In this interactive guide, we shed some light on common misconceptions around the role financial data plays in people’s lives and how a credit score is constructed. We also explain the concept of your “Data Self” – the version of you out there made up entirely of your financial data – and offer some advice as to how to best work with that “Data Self” so that it’s in the best shape it can be.”

 

“Each time you interact with the digital world, whether that’s through a phone, computer, tablet, or any connected device, you’re creating data with your activity.”

“Personal data means any piece of information that can be used to identify an individual. You create it when you’re exercising, listening to music online, messaging friends or doing anything that involves a smartphone or connected device.”

“An increasing number of everyday objects are now connected to the Internet, meaning the quantity of data created continues to grow. By 2020, Intel estimates that there will be 200 billion Internet-connected devices on the planet. It might not be long before your fridge, car or washing machine are hooked up to the Internet and generating personal data, (or perhaps they already are).”

“At Experian we process over 1.5 billion records a year. We’re passionate about data – as a force for good, as a tool to empower and improve people’s lives – but we know it’s not always the most exciting topic for you. That’s why we commissioned research asking the views of 3,000 people in the UK about personal data, with a particular focus on their attitudes to their financial data footprint. In the following sections we’ll talk more about Brits’ attitudes to their personal data, and look in more detail at the financial data that goes to make up a credit report – your Data Self.”

“Personal data means any piece of information that can be used to identify an individual.

“We’re a nation of “egosurfers”

The study found that people are naturally curious about what their data says about them. There’s even a name for it – “egosurfing”, which describes the activity of looking up your name on a search engine. Nearly three quarters (72%) have searched for themselves online.”

“On average, people update their online image 168 times a year – that’s a big increase in their personal data footprint.”

“The most common reason for “egosurfing” was curiosity (81%). Far fewer people (21%) said they searched for themselves to help protect their online reputation. Other reasons given included research into ancestry, checking who has the same name as them and “for a laugh”.”

“Many of those surveyed also enjoy having a nose around for online information about friends, family and acquaintances, with 71% admitting to checking someone out online before meeting them. A further 60% have searched for someone they went to school with but no longer speak to, and 39% have searched for an ex-partner online.”

“The younger generation in particular value their online profile; 24% of 16-24 year olds care a great deal about it, compared to just 13% of those aged 55 or over. It may not come as a surprise that those aged 25-34 are also savvier about the value their data brings and feel more in control of it than their elders; 86% of this age group think their online data is important to them, compared to 61% of those over 55.”

“Those under 25 are much more likely to take a laissez-faire approach to reviewing the conditions of sharing their data to download a new app; 39% of 16-24 year olds never read the Ts&Cs, compared to only 16% of those over 55.”

“Although many people are drawn to researching their online profiles, and those of others, understanding what their financial data says about them does not hold the same appeal. The study found that 24% of people are bored by the topic of financial data and a fifth never talk about their financial data. Some find it confusing (19%); others are fearful of it (9%).”

16% of people believe they have no influence on their financial data. That’s a misconception. Whether you are looking for a mortgage, planning a family or making any life-changing decision, your financial data matters because it influences what types of deals and offers you can access. While it might sound dull to spend time understanding how to manage your financial data, it can actually be life-changing.”

“There’s another version of you made up entirely of your financial data, which we call your “Data Self”. It’s made up of your credit card transactions, phone contracts, mortgages and loans, as well as other financial information.”

Your Data Self can be really important when it comes to the big financial events and decisions you face in your life. That’s because it is used to create your credit report; important information that lenders use to decide whether you can access the services or products you want. (See section below “Your credit report and your Data Self”). Your Data Self is constantly evolving, based on your credit information, which includes your borrowing activity.”

“Understanding and improving your Data Self could make all the difference between getting a ‘yes’ or a ‘no’ from lenders, and could even help you unlock better borrowing rates. That’s because lenders’ decisions about whether you can afford something are made from the financial data available about you.”

“Checking your credit score with a credit reference agency on a regular basis is an important step in taking control of your Data Self, as it gives an idea of how lenders may view you. Currently a fifth of people never talk about their financial data.”

A credit score gives you an idea of how lenders may view your Data Self for a broad range of important services and life essentials such as credit cards, loans, mortgages, car financing and even mobile phone contracts. In essence, it is a number that reflects the likelihood of you paying credit back.”

“Your credit report is used to calculate your Experian Credit Score. Your report brings together data on your previous borrowing over the last six years to give an overview of your credit history – the same information lenders could use when they call upon your Data Self. “

“When you’re making financial decisions with a partner, you need to understand the link between your Data Self and theirs. The truth is you only become financially linked to someone when you apply for joint credit or when you open a joint account. These financial associations remain on your credit report until you tell the credit reference agency that the link has ended. It is important to break the link to previous partners with whom you were financially linked.”

‘The Data Self (A Dialectic)’

“Rob Horning has been working on the topic of the “Data Self.” His project has a close parallel to my own work and after reading his latest post, I’d like to jump in and offer a conceptual distinction for thinking about the intersection of the online/data/Profile and the offline/Person.”

“The problem is that our online presence is too often seen as only the byproduct of our offline selves. Sometimes we talk about the way online profiles are passive reflections of who we are and what we do and other times we acknowledge our profiles are also partly performative adjustments to the “reality” of the person.”

“…the discussion of individuals creating this content what is often neglected is how the individual, in all of their offline experience, behavior and existence, is simultaneously being created by this very online data. We cannot describe how a person creates their Profile without always acknowledging how the Profile creates the person.”

“…I use the term profile(lower-case ‘p’) to mean our presence on any specific web service, e.g., our Twitter or Facebook profiles. I use the term Profile (capital ‘P’) to refer to the aggregate set of our entire online presence across all profiles including data we have uploaded or others have gathered.”

“And let me call the “agentic bias” the tendency to conceptually grant too much power to individuals to create their online Profiles by neglecting the ways in which individuals are simultaneously being created by their digital presence. Lots of social media writing, academic and popular, looks like this:

“Many otherwise terrific articles about the self, identity and social media suffer from this bias.”

“For now, I want to focus on responding to and joining in on Rob Horning’s work on “the data self.” He makes many useful points, but fundamentally conceptualizes “data” and “self” in a manner in which the latter causally precedes the former (I happen to know he doesn’t like that ‘latter-former’ turn of phrase).”

“Horning describes how we “convert ourselves into data”; we are “monitoring [our] vital statistics and uploading them for analysis and aggregation.” Further, Horning goes on to say,

“data collection is slowly becoming the ideological basis of the self”

“interactions within social networks are now easily captured

“The assumption is that by letting Facebook capture and process everything, a more reliable version of the self than our own memory can give us will be produced.”

And Horning cites Facebook as saying “the Timeline to be a place for self-expression: A way for users to reveal who they are and what their lives are about”

(all emphases mine)

The “data self” as described here has everything to do with how self creates, produces, collects and revels itself through data. This is indeed an important concern, and, to be clear, there is far more I agree with than disagree with in Horning’s analyses.”

“…lots of attention has been given to how the self creates the data, what I called the agentic bias above; but what about when this data also creates the self? Both considerations must be simultaneously taken into account to understand either.

Instead of an agentic bias, I propose a dialectical understanding of the causality between the individual/offline/self and the data/online/Profile:

“Indeed, the name Cyborgology makes explicit reference to Donna Haraway’s cyborg theory of bodies and technology as enmeshed. Further, I have written extensively on what I call “augmented reality,” the perspective that views the on and offline as enmeshed, opposed to the “digital dualist” bias to view atoms and bits as separate. To fully theorize the self from the “augmented” perspective, one must rigorously take into account the data-flesh-enmeshment from both directions.”

“I describe how one great power of social media is not just what happens to us when logged in uploading data about ourselves and our lives, but also how sites like Facebook change how we view the world even when logged off and not staring at some glowing rectangle; what I call The Facebook Eye. To only focus on how the self produces data is to miss how data influence our experience of the world; how we behave within it and how data creates that same self that creates the data.”

“Let’s take some concrete examples:

When listening to music on Spotify, a streaming service that syncs with and publishes to one’s Facebook profile, I am publishing that listening-data to Facebook for others to see. It becomes part of my Profile. But to end the story here is to suffer from the agentic bias. Let’s put the other causal arrow back in and think dialectically: because my Profile contains listening behaviors that I know are being judged by others, I may choose to listen to slightly different music to “give off” the impression I wish to portray. More than just a better-than-accurate presentation of self, the fact that the Profile exists changes my experience and behavior as a person.”

“But we must go further than just potential changes in behavior. What I find most interesting is how the Profile changes our experience of that behavior.”

“We experience a concert differently when we know we can post photos on Facebook and videos on YouTube; hence the music-venue-plague of glowing document-screens held high instead of hands. We see the food we just prepared differently when we know we can post a photo of an especially delicious-looking meal to Facebook. As I’ve posed before: think of traveling with and without a camera in your hand: the experience is at least slightly different. Today, we are always living with the camera in-hand; we can always document our lives via status updates, tweets, check-ins, photos, videos, etc. Like those on reality TV, social media users are deeply influenced by the fact of near omnipresent documentation potential.”

“…the conceptual opposite of the agentic bias would be a structure-bias that views people as only the result of our Profiles. Once, on a subway, I heard a woman claim that “the real world is the place where we take pictures for Facebook.” But this is probably going to far, right?”

“To conclude, and to provide a last probe to Rob, the implications of all this is that we cannot continue to view the Person as the temporal and causal antecedent and the Profile as something that is the subsequent result. We have clear evidence that the person is also being co-constructed by the Profile. Experience creates documentation and documentation creates experience.”

‘Data, Self & Society’

“The research group “Data, Self and Society” at the Consumer Society Research Centre explores how datafication, referring to the conversion of aspects of life into quantified data, is promoted, practiced, analyzed and received in the contemporary world. Current research falls under three thematic areas:

Self-tracking and living with data:

“The rapidly expanding research on wearables and self-tracking practices reflects the rise in the use of digital technology in the everyday. The defining characteristic of self-tracking is that people are confronted with their own personal information, including sleep, steps, stress levels, and eating. Self-tracking relies on personal data streams in an attempt to slice life into comprehensible and controllable units.”

” Recent publications discuss co-evolving with self-tracking technologies, forms of emotion tracking and the situational objectivity characteristic to personal metrics. Demonstrating that the study of data practices and datafication benefits from a more thorough analysis of the everyday, the aim is to critically address the active and ever-changing work around personal data streams.”

Digital methods and data explorations

“The analysis of large data sets calls for new kind of reflexivity from researchers, including novel research perspectives. In recent publications, we study the datafication of hate and explore the Suomi24-dataset through the concept-metaphor of broken data. We utilize data analytics in an attempt to develop tools and frameworks for understanding how conversational landscapes and topics develop in time. By identifying online practices and engagements, we promote the development and understanding of digital research methods which will allow investigators to gain a more detailed view of the production and analysis of data and deepen the understanding of how temporal aspects of social life, or social media discussions affect, guide, and constrain their participants.”

“Smarter Social Media Analytics studies and develops methods to identify trends and phenomena using large social media datasets. To this end, we use the full data set of online forum Suomi24 (see above) and the full data set collected and owned by Futusome Oy, covering approximately 1 billion Finnish language messages from different social media services (2001-2016). As a comparative data set we use the representative survey data collected by Taloustutkimus Oy (2007-2016). By cross-investigating these datasets using both computational and qualitative methods, we develop and validate algorithms to identify and explain emerging trends and individual phenomena from the online conversations. Currently we are focusing on various food-related trends. Simultaneously, using an ethnographic approach the project explores how data is used and transformed to knowledge within the data analytics companies, and what are the epistemological considerations that frame data, data analysis methods and visualizations.”

Datafied power and digital citizens

“The third thematic area explores forms of datafied power and their consequences. We study the evolution of the data economy, datafication of health, and reactions to surveillance economy. The work builds on the notion that software and algorithms produce data and work with it in particular ways and, by doing so, have social, political and economic implications.”

“We follow market developments by exploring the visions and aims of start-up companies and citizen-led co-operatives that aim to modify, with their technologies, platforms and business approaches, the current data economy landscape and forms of digital work.”

“Further research analyses patents related to personal data uses and user/consumer action in relation to personal data management models, from blockchain-based distributed models to dominant US tech-giant models. The project called Becoming Data Citizens explores social and political alternatives that aim at promoting more transparent and citizen-centric data use. We investigate data activism by developing the notion of non-data-centric data activism.”

“When an earthquake occurred in the Bay Area, California in the night of August 2014, many people living in the area were monitoring their sleep patterns using a wearable device. The developers of one of these devices, the Jawbone Up, released the accumulated data from these users’ sleep that night.” (62)

“While these data are perhaps unsurprising and banal in the insights they offer, they are signifi cant in another way. They represent the use of accumulated data from tens of thousands of people worldwide who are using digital devices to engage in self-monitoring of their everyday routines, behaviours and practices.” (62)

“The reporting of these personal data by Jawbone demonstrates not only that people are tracking their sleep using a wearable digital device such as the company’s Up, but that these personal data may be aggregated and used by developers for their own purposes as part of publicising their product and demonstrating how information about an individual’s private behaviour (in this case, their sleeping patterns) can be part of gathering insights into populations.” (62-63)

“Data is a keyword in discourses on self-tracking. Most recently and noticeably, detailed quantifi able data have become valorised above other forms of information about one’s life, health and wellbeing. I will discuss the valorisation of quantifi cation as a self-tracking data practice, but I also go on to examine alternative data practices with which some people are experimenting as part of self-tracking strategies.” (63)

“The advent of digital technologies able to assist in the collecting, measuring, computation and display of these data has been vitally important in promoting the cause of self-tracking. While people have been able to monitor and measure aspects of their bodies and selves using non-digital technologies for centuries, mobile digital devices connected to the internet have facilitated the ever more detailed measurement and monitoring of the body and everyday life in real time and the analysis, presentation and sharing of these data.” (63)

Digital devices are employed to collect numbers on body functions, emotional states, sexual and social encounters, work productivity, physical activities and geo-location, to name just some variables. While much of these data are collected and displayed in quantitative form, several others are qualitative, using words, images and objects to record and display personal details.” (63)

“Self-tracking is not only a technology of the self, but it is also a data practice. Self-tracked data are merely one form of a vast array of methods and strategies related to gathering, interpreting, portraying and acting on data. In an increasingly sensor-based and surveillance society, in which digital data are continually gathered on people as they use digital technologies and move around in space and place, massive datasets are generated. These datasets are having an increasingly important role in shaping policy, commercial dealings, education, social welfare and healthcare, the management of groups and populations and in individuals’ personal and everyday…  (63-)

   

 

“…

“Since interactions within social networks are now easily captured and standardized, the quantifiable data thereby produced have become far more constitutive of identity.”

“… 

“The assumption is that by letting Facebook capture and process everything, a more reliable version of the self than our own memory can give us will be produced.”

  

   

“The more work we put into making a coherent story out of the data Facebook collects, the more useful, marketable information we give them.”

  

‘List of Countries by Credit Rating’

  • This is a visual representation that depicts “long-term foreign currency credit ratings for sovereign bonds as reported by the three major credit rating agencies: Standard & Poor’s, Fitch, and Moody’s. The ratings of DBRS, China Chengxin, Dagong, JCR are also included.” (List of Countries by Credit Rating, 2018)

Credit Rating Break Down:

  • SP – Investment bond [BBB- or higher]: United Kingdom: (Rating= AA) (Outlook = Negative)
  • Fitch – Investment bond [BBB- or higher]: United Kingdom: (Rating = AA) (Outlook = Negative)
  • Moodys – Investment bond [Baa3 or higher]: United Kingdom (Rating = Aaa) (Outlook = Stable)
  • DBRS – Investment bond [BBB- or higher] : United Kingdom (Rating = AAA) (Outlook = Stable)
  • JCR – Nationally Recognised statistical organisation based in Japan: United Kingdom (Rating = AAA) (Outlook = Stable)

 

Are we consumed by our consumption?

From data fetishism to quantifying selves: Self-tracking practices and the other values of data:

“This article foregrounds the ways in which members of the Quantified Self ascribe value and meaning to the data they generate in self-tracking practices. We argue that the widespread idea that what draws self-trackers to numerical data is its perceived power of truth and objectivity—a so-called “data fetishism”—is limiting.” (2016: 1695)

“we describe three ways in which self-trackers attribute meaning to their datagathering practices which escape this data fetishist critique: self-tracking as a practice of mindfulness, as a means of resistance against social norms, and as a communicative and narrative aid. In light of this active engagement with data, we suggest that it makes more sense to view these practitioners as “quantifying selves.” (2016: 1696)

““Data is the new oil” is a phrase that has come to express the growing value of data in an era where Big Data promises to generate new insights and solutions for everything from healthcare to city planning.” (2016: 1696)

“…the data sets that make up Big Data are always creations of human design, and thus are always implicated in social relations and power dynamics (Andrejevic, 2014; boyd and Crawford, 2012; Crawford et al., 2014; Van Dijk, 2014).” (2016: 1696)

“Where the question of the value of data for those who generate it is addressed, this value is typically understood as residing in the aura of neutrality and objectivity that numbers convey, and their role in a will to (quantified) truth (Lupton, 2013a, 2013b; Morozov, 2013).” (2016: 1696)

“Avid self-trackers, such as members of what is known as the Quantified Self (QS) movement, are thus typically portrayed as “data fetishists,” enamored by the authority of numerical data and motivated by a desire to control and optimize the overwhelming complexity and uncertainty of life (Dormehl, 2014; Morozov, 2013; Rettner, 2014). Data, in such accounts, are framed as inherently reductionist, and practices of quantification are seen as a tool in the quest to reduce all phenomena, no matter how complex, to numbers while displacing other forms of meaningful expression (Lupton, 2015).” (2016: 1696)

“Instead, more effort needs to be made to understand the myriad ways in which data are deemed valuable and meaningful for self-trackers themselves. Focusing our analysis on the self-tracking practices of members of the QS community, we argue that an ethnographic focus on self-tracking practices (Mol, 2002) offers a perspective that moves beyond the limiting frameworks in which self-tracking is conventionally understood.” (2016: 1696)

“…we suggest that rather than seeking to achieve a perfectly optimized, calculable and controlling “quantified self,” it makes more sense to look at members of this movement as “quantifying selves,” who actively engage with data and render it meaningful in and through self-tracking practices.” (2016: 1696 – 1697)

“…we unpack the main analytical components of the data fetishist critique that is widely held in academic and popular accounts of QS. Next, we describe how QSers attribute meaning to their self-tracking practices in ways that escape the fetishist critique. Our overall aim is to contribute to the growing critical conversation on the culture of Big Data, but by means of a broad, ethnographically grounded understanding of the variegated ways in which people interact with and become involved with their data in everyday life.” (2016: 1697)

“In light of Wolf’s words, self-tracking holds the promise of identifying signals and patterns that remain hidden when one relies solely on the limited toolbox of human senses. Measurement, quantification, graphs and spreadsheets do not lie; their emotional detachment and arithmetic precision, both painful and trustworthy, can render these patterns visible, knowable and, hopefully, manageable. Numbers, in this sense, with their particular appeal of scientific objectivity, seem to provide a privileged access to the truth, and generating and tracking them may, as the movement’s self-proclaimed motto upholds, lead to “self-knowledge through numbers.” (2016: 1697)

“Self-tracking works on the basis of categories or indicators that act as proxies for what are commonly very messy and rich phenomena, from “mood” to “health” to “productivity.” In the process, critics protest, an entire world of human, social and environmental complexity may get lost.” (2016: 1967)

“Deborah Lupton (2015) argues that such apps suggest that women can achieve more accurate knowledge about their bodies than they did with non-digital means of tracking such as experiencing and observing their bodies’ signs, rhythms and sensations. This “imperialistic streak” of quantification, as Morozov calls it, implies that as one’s trust in numbers grows, one’s trust in subjective, embodied and intuitive knowledge decreases. As Morozov (2013) cautions, “Human experience, run through the quantification mill, is reduced to little more than a stream of silent and mind-numbing bytes” (p. 256).” (2016: 1697)

“More recently, a growing number of sociological analyses are demonstrating that no less than their forebears, the generation, collection and analysis of digital data is situated in powerful public and private sector institutions, that may use these for aims of government surveillance and online advertising (Andrejevic, 2014; boyd and Crawford, 2012). For some theorists (e.g. Cheney-Lippold, 2011), this marks a shift to a subtle yet no less pervasive form of control, via the digital constructions of “new algorithmic identities.” ” (2016: 1697)

“The commitment to self-improvement that QSers subject themselves to can thus easily be read against a backdrop of the neoliberal project of citizen activation and responsibilization (Ayo, 2012; Lupton, 2012; Sharon, 2015). As data fetishists, self-trackers are commonly considered to be unaware or unconcerned by the normative assumptions and diverse sinister uses their data-generating efforts can be put to.” (2016:1697)

“We did so while organizing break-out sessions at QS conferences, interviewing active participants and sharing our thoughts online.3 During this time, we became increasingly aware of how detached perceptions of the QS movement, and “tracking culture” in general, can be from the different forms of meaning-making related to self-tracking in the context of this network.” (2016: 1697)

” …the stereotypical image of the QSer is of someone obsessively datafying the self into a calculable, objectified quantified self. Yet, we observed the QS movement to be a heterogeneous network of people actively exploring many different other effects, affects and objectives of tracking practices, suggesting that it makes more sense to speak of QS as a loosely knit network of “quantifying selves.” QS is home to different types of trackers (from the high-tech to the low-tech, the occasional to the intensive tracker, the purposeful to the “random” tracker, the private to the public tracker), to different kinds of objectives and goals (from tracking the effects of medication on Parkinson’s or diabetes, to tracking the effects of music, the weather and particular types of food on one’s mental state), and to many different types of tracking methods.” (2016: 1697)

“What we found to be the most significant common denominator to these various tracking practices was the cultivation of reflection on and through tracking. To this end, different formats define the contours of various QS gatherings, from “show & tell” talks, to break-out sessions, to online discussions around specific topics.” (2016: 1697)

“…we discovered three other forms of meaning-making that QSers drew on as part of their selftracking practices, which we discuss below: self-tracking as a practice of mindfulness; as a means of resistance against and a remaking of dominant social norms and conventions; and as a narrative and communicative practice that can articulate experiences at the boundaries of different domains of knowledge. (2016: 1699)

“…one of the main concerns underlying the data fetishist critique is that a trust in numbers will trump other forms of subjective, intuitive and embodied knowledge.” (2016: 1699)

“…while new technologies always help create new conditions for human behavior, how this dynamic unfolds is not determined a priori (Verbeek, 2011). The self-trackers whom we listened to often spoke about this relationship as a tension, or a negotiation, that produces meaning.” (2016: 1699)

“Because the “work of tracking can be a lot,” he explains, “you sometimes simplify,” “avoid[ing] complex recipes and prioritiz[ing] food that best fits the capabilities of [your] databases and sensors.” But for this participant, this simplification never came at the expense of losing his intuitive sense of food. ” (2016: 1700)

“…he told us, “increased [his] mindfulness”—in the context of a relationship to food that had been mind-less. This connection to mindfulness practices is more than coincidental, as other commentators of the QS movement have also observed (Boesel, 2013).” (2016: 1700)

“…the concept of mindfulness has by now become secularized and merged with a host of Western institutional traditions, from health, to business, psychology, and, now, also to technological practices (Zandbergen, 2012).” (2016: 1700)

“In the context of QS, participants often use the term to refer to the way in which the practice of tracking helps them to focus their awareness on habits, unconscious actions, and patterns that are typically unperceivable.” (2016: 1700)

“In such examples, numerical data are not at all the end-goal of tracking; they are more like an unsophisticated, intermediate stage towards more augmented senses. For some self-trackers, the cultivation of this awareness is more significant than the actual data generated by tracking.” (2016′: 1700)

“In 2004, the conceptual artist Alberto Frigo began a project to track all his daily activities by recording every object he held in his right hand. “If I keep up the project until I turn 60,” Alberto explains, “I will have photographed 1.000.000 objects and could thus claim to have some kind of DNA code of my life” (QS14). In the decade Alberto has been at it, he has also started tracking his dreams, songs he hears during the day, his social surroundings and the weather, all of which he brings together using various media such as photography, notes and audio-recordings (see 2004-2040.com).” (2016: 1700 – 1701)

“Yet for Alberto, the significance of his tracking practices lies not in some truth that his databases may reflect back at him. As he told us, he rarely looks back at his data. Nor does he attempt to automate and perfect his data-gathering in the hope of achieving ever more complete and objective information. Rather, he invests in imperfect and time-consuming manual registrations. As we discuss his project over lunch, Alberto stops, pulls out a simple camera and photographs the spoon he is about to use. His choice of this somewhat outdated and cumbersome medium is telling, as it becomes clear that the ultimate meaning of self-tracking for Alberto resides in the very process of recording. He describes his tracking as a way of “activating himself,” and creating a “playful engagement with an otherwise dull surrounding.”” (2016: 1701)

“As he explains, the act of constantly recording allows him to see more—interesting trash, fantastic cloud shapes, street musicians—and to appreciate as special an environment that others may regard as mundane, dull and ordinary. In this way, Alberto describes the meaning attributed by him to his tracking activities in very different terms than those usually ascribed to him, for example, as the overriding or replacement of the embodied sensorial, “real” world by a “permanent digital life” (cf. Preston, 2014).” (2016: 1701)

“Dana Greenfield designed her self-tracking project, Leaning into Grief, around the death of her mother, as a means of tracking her grief. Using a custom-made digital spreadsheet, she logs various experiences related to her grief—sights, conversations, events that elicit memories of her mother, comments on them, where they took place, and the mood she associates with them. Similarly to Alberto’s, Dana’s project is as much about concretizing her mother’s legacy in her own life as it is about cultivating an awareness of the experience of moving through loss.” (2016: 1701)

“The practice of tracking here opens up a reflective space in which memories can be “explored and cherished,” and in which grief can “work itself out.” As for Alberto, the act of logging the data becomes more meaningful—and therapeutic—than the actual data-as-memorabilia that is its content.” (2016: 1701)

“…the mindfulness emphasis on being “in tune” with one’s personal sensations, thoughts and feelings speaks out against a mainstream culture that is seen as discouraging people from being active producers of this world.” (2016: 1701)

“Alberto presents his tracking practices as a way of gaining access to “hidden processes” that are typically inaccessible: “When you are photographing the tools … [you] want to be authentic … to know a bit of the processes that are hidden from you, along the way, by the society in which one grows.” For Alberto, self-tracking becomes a way of revealing the “nuts and bolts” of the world. Dana also attributes value to her tracking practices in opposition to widespread societal expectations—of how one should grieve, how long it should take and how much of a focus it should be.” (2016: 1702)

” …self-tracking takes on an oppositional value, by which practitioners enact various forms of agency and autonomy vis-a-vis a larger society, its institutions and corporations, by resisting and remaking social norms and conventions.” (2016: 17002)

“For her, the choice to actively track herself is, as she put it, “liberating”. One of the ways in which self-trackers enact this autonomy is by tweaking the hardware, software and analytical categories set by their tracking tools.” (2016: 17002)

“Alberto’s decision to use outdated tracking technologies and self-written software is informed by a rejection of proprietary software, hardware and data platforms that are designed and owned by private corporations and that, he feels, turn him into a passive consumer. Not complying for Alberto means one has to “keep on, move on, tweak things.”…” (2016: 1702)

“Larry Smarr, for example, whose self-tracking led him to detect he had Crohn’s disease before his doctors did, is often referred to as somewhat of a QS hero. Smarr tracked in defiance of his doctors, who believed nothing was wrong with him.” (2016: 1702)

“Since the 1960s, in this region, digitization processes were informed by a subversive discourse of (digital) technologies enabling people to “break through” conventional and oppressive ways of knowing the world. The emphasis placed on the personal appropriation of these technologies—as opposed to simply consuming products built by others—has been an important element of this subversive technological culture.” (2016: 1703)

“In line with Theodore Nelson’s (1974) contention that “if you can’t control the button, the button will control you,” technology-minded activists embraced the development of the smaller, cheaper and more accessible personal computer as a tool that would provide control over knowledge, communication and perception in general to more people.” (2016: 1703)

“While QS is currently an international network bringing together very diverse people from different backgrounds, it makes sense to root it in this longer tradition of high-tech counterculturalism and digital resistance.” (2016: 1703)

“As Wolf told us, from the outside, it may seem like QS is an integral part of the normalization of surveillance and compliance. But, “here it’s quite different. Here you have conversations about, ‘how do you protect your data?’, ‘how do you get your data?’ ‘how do you imbue your practices of formalizing your experiences with a spirit of autonomy?’” Reflecting this awareness, typically, QS conferences include a significant number of sessions devoted to critical discussions on access to data, data management, data ownership and privacy.” (2016: 1703)

“Yet, we suggest that this type of problematization should also apply to the counter-trope of QSers as data fetishists uncritically internalizing societal norms. As we have shown, QSers challenge and remodel the assumptions, norms and categories that are built into tracking devices, sometimes quite literally as they assemble their own projects. As such, the QS movement is best described as one that both feeds into mainstream Big Data culture and that continuously resists, reshapes and redefines it (Nafus and Sherman, 2014; Neff and Nafus, 2016).” (2016: 1703)

“In the following, we discuss the notion that self-tracking is also about exploring new forms of expression that do not privilege numbers a priori, but integrate and combine the seemingly objective language of numerical data with other forms, as a means of meaningfully communicating in and navigating a world that speaks both.” (2016: 1704)

“Data fetishism seems to be at its strongest when data pertains to one’s self. But while the QS official tagline is indeed “self-knowledge through numbers,” QS is also characterized by a strong communal and communicative quality.” (2016: 1704)

“Standing on stage, self-trackers speak about painful episodes in their lives (depression, divorce, disease); they expose their dreams, their diary entries and their meditation practices, and they reveal minutiae about their physical ailments and their struggles with weight and mental well-being.” (2016: 1704)

“Another self-tracker used the term “mingling” as a way of describing the relationship between the quantitative data generated on her device and subjective terminology. Data become “signals,” that are added on to, or into, subjective narratives, in the form of what she calls “digital storytelling”…” (2016: 1704)

self-tracking is not just instrumental in identity construction but also serves to mediate between and across various realms of meaning and knowledge, such as appropriate and taboo topics of conversation, diagnostic fields and subjective and objective experiences of health and illness.(2016: 1705)

“The qualified self refers to processes by which quantified data are interpreted, transformed and integrated into qualitative narratives. Jenny Davis (2013) argues that this term better represents the actual entanglements and negotiations between quantitative data and interpretive schemes that create meaning for self-trackers: “If self-quantifiers are seeking self-knowledge through numbers, then narratives and subjective interpretations are the mechanisms by which data morphs into selves.” Data in these types of self-tracking practices are a new element in an aesthetic and continuous process of identity construction. It is not just used to learn about oneself but also to construct stories about oneself.” (2016: 1705)

“In these examples, quantified data helped render aspects of a private, subjective and somewhat inaccessible world of feelings and problems more tangible and comparable. Understood as a narrative and communicative practice, self-generated data may thus enable the social sharing of private experiences and mediate between subjective experiences of physical or mental health and more objectifying framings of health and ill-health.” (2016: 1705)

“…we argued that insofar as the value of data has become a main focus of critical data studies, more attention needs to be paid to the ways in which data are valuable and meaningful for those individuals…” (2016: 1705-1706)

“…we argued that the idea that what draws self-trackers to numerical data is its perceived power of truth and objectivity, which underlies the “data fetishist” critique, only offers a partial explanation of the appeal self-tracking has for trackers.” (2016: 1706)

“The data fetishist critique cautions that quantification tends to reduce all phenomena to numbers, to displace other forms of meaningful expression, and that numbers, although seemingly neutral, always imply tacit, normative assumptions.” (2016: 1706)

“Self-tracking can be a practice of mindfulness, in which sensorial and emotional experiences of being in the world are not replaced by automated, quantified registers but are actually given more space, heightening one’s awareness of the everyday. Self-tracking can be a practice of resistance, in which practitioners enact various forms of agency and opposition in relation to social norms and societal institutions and corporations.” (2016: 1706)

“…self-tracking can be a communicative and narrative practice, where data are used to enrich self-narratives, to share experiences that may otherwise be difficult to convey and to mediate across realms of knowledge. Data are deemed valuable in these practices insofar as they may extend (rather than displace) one’s senses, they may enable users to resist (rather than comply with) normalization and they may supplement (rather than solely constrain) what can be said.” (2016:1706)

“…self-tracking practices thus reveals that alongside the figure of the quantified self, as the perfected, optimized, calculable and controlling subject and object of self-tracking, emerges a quantifying self. The quantifying self ascribes meaning to self-tracking and the data generated by it through a process of continuous negotiation with self-tracking methods and tools (literally dismantling them at times), of constant interaction with the daily environment, and of involvement with others who share similar interests.” (2016: 1706)

“By foregrounding this active engagement, we theorize the QS movement as one that both feeds into and contests the culture of Big Data, reproduces and meaningfully escapes it, thus contributing to its (re)definition.” (2016: 1706)

“…QS may be seen as a network of people who seek to find new ways of navigating, finding agency in, and making sense of an increasingly datafied world.” (2016: 1706)

The diverse domains of quantified selves: self-tracking modes and dataveillance:

 

“There is evidence that the personal data that are generated by the digital surveillance of individuals (dataveillance) are now used by a range of actors and agencies in diverse contexts. This paper examines the ‘function creep’ of self-tracking by outlining five modes that have emerged: private, communal, pushed, imposed and exploited. The analysis draws upon theoretical perspectives on concepts of selfhood, citizenship, dataveillance and the global digital data economy in discussing the wider sociocultural implications of the emergence and development of these modes of selftracking.” (2016: 101)

“Notions of selfhood, embodiment and social relations have increasingly become developed via digital technologies. Many social and commercial interactions now take place online; most homes, educational settings, health care institutions, security and policing enterprises and workplaces have become digitized to a greater or lesser degree. Physical spaces have become embedded with sensors that can detect humans’ movements and other activities.” (2016: 101)

“A global knowledge economy has developed that relies in part on the generation and use of the data that are collected by digital technologies.” (2016: 102)

“Indeed, it has been contended by some theorists that power now operates principally via digital modes of communication. In this context, the software, hardware devices, the digital data that they generate and the algorithms that make sense of these data have become key actors in constituting and exploiting knowledges (Amoore & Piotukh, 2015; Kitchin, 2014; Lash, 2007; Thrift, 2005).” (2016: 102)

“Self-tracking is also referred to as lifelogging, personal analytics and personal informatics. In recent years, ‘the quantified self’ has become a popular term to describe self-tracking in the wake of the establishment of the Quantified Self website and movement, involving online interactions and face-to-face meetings and conferences. Once the data are collected, self-tracking practices typically incorporate organization, analysis, interpretation and representation of the data (such as producing statistics or graphs and other data visualizations) to make sense of them, and efforts to determine how these data can offer insights for the user’s life.” (2016: 102)

“With the advent of mobile and wearable digital devices and associated software, such details can be more readily collected, analysed, searched, aggregated, visualized and compared with others’ data than ever before.” (2016: 102)

“I contend that these technologies are raising new issues concerning the use of people’s personal information about their lives and bodies. These include the ways in which this information is purposed and repurposed as part of the global digital knowledge economy, data privacy and security issues and the implications for concepts of selfhood and citizenship.” (2016: 102)

“Digitized self-tracking is a form of dataveillance, or the watching of people using technologies that generate data, increasingly in digitized formats (van Dijck, 2014; Raley, 2013). Digitized self-tracking technologies promote a culture of dataveillance and offer diverse methods by which it is undertaken.” (2016: 102)

“Many dataveillance activities monitor people in ways of which they may be unaware: closed-circuit television (CCTV) camera and sensormonitoring of people’s movements in public spaces, national security agencies’ and policing bodies’ surveillance of communication metadata and internet companies’ commercial data-harvesting activities, for example.” (2016: 102)

‘Dataveillance’ – invasive, unaware, clandestine ways of gathering data, e.g. CCTV, Sensor capturing in public spaces, policing bodies, commercial data harvesting advertising

‘Self Tracking’ – Involves subjects knowingly engage with and examine their own personal information, often as a means of optimising or increasing mindfulness or efficiency within daily living. Self-Tracking can also be an inherently social excersize as people are often invited to compare and contrast data collected. (Self-Surveillance)

“In contrast, self-tracking involves the data subjects themselves being confronted with their own personal information and, in many cases, being invited to engage with this information in some manner as part of optimizing and improving their lives. They are therefore engaging in self-surveillance.” (2016: 103)

“Social surveillance is itself an element of ‘sousveillance’, or ‘watching from below’ (Mann & Ferenbok, 2013), which differs from classic surveillance, or ‘watching from above’. The use of digital self-tracking technologies blurs the spatial boundaries between public and private surveillance, bringing public surveillance into the domestic sphere but also often extending private surveillance out into public domains.” (2016: 103)

“The concept and practices of self-tracking are now dispersing rapidly into multiple social domains, displaying evidence of ‘function creep’. Increasingly, the collection and analysis of personal data via self-tracking practices are advocated and implemented in many social contexts and institutions, including the workplace education, medicine and public health, insurance, marketing and commerce, energy sustainability initiatives, the military, citizen science and urban planning and management.” (2016: 103)

“As yet, there has been no sustained examination of the spreading out of selftracking cultures and practices from the purely personal into multiple social domains.” (2016: 103)

“…focusing on a typology I have developed of the five distinctive modes of self-tracking that have emerged in recent times. These are private, pushed, communal, imposed and exploited self-tracking. These categories are for heuristic purposes – a means to distinguish and elaborate on the ways in which self-tracking has become diversified. There are, of course, intersections and recursive relationships between each of these self-tracking modes.” (2016: 103)

“What I call ‘private self-tracking’ is undertaken for voluntary and personal reasons that are self-initiated. ‘Pushed self-tracking’ involves encouragement for people to monitor themselves from other agencies, while the mode of ‘communal self-tracking’ relies on people sharing their personal information with others. ‘Imposed self-tracking’ involves moving from encouragement to requiring people to collect or engage with data about themselves in situations in which they have little choice. The ‘exploited self-tracking’ mode represents the use of personal data by other actors and agencies for their own purposes, either overtly or covertly.” (2016: 103)

“Traditional self-tracking practices have included age-old strategies such as journaling and diary-keeping.” (2016: 104)

“Mobile digital devices connected to the internet, devices and environments that are fitted with digital sensors and the possibilities for data archiving and sharing that are afforded by computing cloud technologies have contributed to the ever more detailed measurement and monitoring of people’s activities, bodies and behaviours in real time. People who engage in self-tracking may use devices that they carry or wear on their bodies or software for their mobile or desktop computers, or they may generate data from ‘smart’ objects with which they interact.” (2016: 104)

“Digitized self-tracking gained greater public attention with the establishment of the Quantified Self movement in 2007 by two Wired magazine editors, Gary Wolf and Kevin Kelly. Wolf and Kelly had noticed that several of their friends and colleagues had begun to engage in digitized self-tracking. They began to host meetings and went on to establish the official website (Quantified Self, 2015) and its associated Quantified Self Labs, a collaboration of users and tool-makers who are interested in working together to share expertise and experiences of self-tracking.” (2016: 104)

“Digitized self-tracking has attracted a high level of attention from developers and entrepreneurs seeking to capitalize on the practice. The technologies themselves are viewed as a major source of potential revenue for digital developers and entrepreneurs, who are taking a keen interest in how best to produce technologies to market to self-trackers and often attend Quantified Self meet-ups and conferences (Boesel, 2013; Nafus & Sherman, 2014).” (2016: 104)

“Tens of thousands of self-tracking apps are available for downloading to smartphones and iPod devices. Smartphones themselves include in-built sensors such as GPS, gyroscopes and accelerometers that can be employed for self-tracking, and iPod Nanos come already equipped with fitness tracking apps such as Nike+ and a pedometer. The new Apple Watch incorporates even more sophisticated biometric monitoring sensors and includes two physical activity apps for self-monitoring.” (2016: 104)

“The term ‘smart cities’ is now often used to encapsulate the intersections of data from smart objects that are both sited in public spaces and used for personal reasons in the private domain, while ‘smart schools’ employ predictive learning analytics to create data profiles on individual learners as part of working towards educational objectives. The discourses and practices contributing to all of these ‘smart’ initiatives continually emphasize the importance not only of generating personal data about individuals but returning these data so that people can reflect – and importantly – act on this information.” (2016: 105)

“A major feature and attraction of self-tracking for many practitioners is using the information they collect on themselves to achieve self-awareness and optimize or improve their lives. The data and the knowledge contained therein are represented as enabling self-tracking practitioners to achieve better health, higher-quality sleep, greater control over mood swings, improved management of chronic conditions, less stress, increased work productivity, better relationships with others and so on.” (2016: 105)

“Private self-tracking, as espoused in the Quantified Self’s goal of ‘self knowledge [sic] through numbers’, is undertaken for purely personal reasons, and the data are kept private or shared only with limited and selected others. Portrayals of self-tracking in the popular media often focus on this mode, with regular references to the ‘narcissism’ or ‘self-experimentation’ that self-tracking supposedly involves (Lupton, 2013c).” (2016: 105 – 106)

“Not only do self-trackers make choices about what data about themselves are important to collect, but they also make sense of and use data in highly specific and acculturated ways. They seek to make connections between diverse sets of data: how diet, meditation or caffeine affects their concentration, for example, or how their mood is influenced by exercise, sleep patterns or geographical location or the specific interactions of all of these variables.” (2016: 106)

“A Nielsen market research survey in early 2014, for example, found that only one in six American adults used wearable devices (including digital fitnesstracking bands) in their daily lives. While women and men were equally likely to use them, owners of fitness bands, in particular, were more likely to have a high income (Nielsen, 2014). Many such individuals associate themselves with the ‘geek’ culture of the Quantified Self movement and associated website and meeting groups (Choe et al., 2015; Nafus & Sherman, 2014; Ruckenstein & Pantzar, 2015).” (2016: 107)

“Pushed self-tracking departs from the private self-tracking mode in that the initial incentive for engaging in dataveillance of the self comes from another actor or agency. Self-monitoring may be taken up more or less voluntarily, but in response to external encouragement or advocating rather than as a wholly self-generated and private initiative.” (2016: 107)

“In pushed self-tracking, those who are advocating others to engage in these practices are often interested in viewing or using participants’ personal data for their own purposes. Self-trackers may not be provided with the opportunity to choose whether to share their information with others.” (2016: 107)

“Advocates for pushed self-tracking are particularly evident in the patient self-care, health promotion and preventive medicine literature. Arguments for persuading people to self-track such bodily features as their body weight and physical activity level, and, in the case of patients with chronic illnesses, such aspects as blood glucose level and blood pressure, are becoming increasingly common in this literature.” (2016:107)

“Self-monitoring is otherwise presented as a form of self-care that allows people with chronic conditions to reduce their interactions with health care providers and become ‘digitally engaged’ (Lupton, 2013a, 2014b). Pushed self-tracking is becoming a feature of children’s lives. In many school settings, software is employed to monitor individual children’s learning, and data analytics is used to track their progress, compare them with other students and to predict their future learning (Selwyn, 2015; Williamson, 2015b).” (2016: 107).

“These ‘exergaming’ technologies are also becoming used in schools as part of physical education and health curricula (Lupton, 2015a; Williamson, 2015a). Children are expected to review their data and make changes if they are defined as deficient or lagging behind compared with the norms established by these types of software.” (2016: 108)

“Many employers are turning to the use of digital self-tracking technologies (‘digital wellness tools’) as part of workplace health promotion programmes or ‘wellness programmes’. Various software packages are now offered to enable employers to monitor their employees’ health and fitness and even their sleep patterns as well as their work habits in the name of good health and worker productivity.” (2016: 108)

“Mobile apps and software programmes that remind employees to get up from their desks and take exercise breaks and to help them manage stress and sleep better are becoming more often used in the workplace (Zamosky, 2014).” (2016: 108)

“Motor vehicle insurers led the way with their telematic devices attached to car engines to monitor driving practices as part of ‘usage-based’ insurance that calculates customized premiums using these data as well as demographic information (NAIC, 2014).” (2016: 108)

“They use social media platforms designed for comparing and sharing personal data and sites such as the Quantified Self website to engage with and learn from other self-trackers. Some attend meet-ups or conferences to engage face-toface with other self-trackers and share their data and evaluations of the value of different techniques and devices for self-tracking.” (2016: 109)

“While there is constant reference to the ‘Quantified Self community’ among members of the Quantified Self movement, this community largely refers to sharing personal data with each other or learning from others’ data or self-tracking or data visualization methods so that one’s own data practices may be improved. Several commentators have begun to refer to ‘the quantified us’ as a way of articulating how the small data produced by self-trackers may be usefully incorporated into large data sets to ‘get more meaning out of our data’ (Ramirez, 2013).” (2016: 109)

“Another portrayal of communal self-tracking is that which is frequently championed in discourses on citizen science, volunteered geographical information, environmental activism, healthy cities and community development. These initiatives, sometimes referred to as ‘citizen sensing’ (Gabrys, 2014), are a form of crowdsourcing.” (2016: 109)

“The concepts of the ‘healthy city’ and the ‘smart city’ are beginning to come together in some attempts to use the digitized sensing and monitoring technologies for health-promoting purposes (Kamel Boulos & Al-Shorbaji, 2014).” (2016: 109-110)

*** Pick up on Page 110 ***

A World without Causation: Big Data and the Coming of Age of Posthumanism:

Chandler, D. (2015) A World without Causation: Big Data and the Coming of Age of Posthumanism. Millenium – Journal od International Studies. [Online]. Vol 43 (3). pp. 833-851

“Data – is capable of changing the ways in which knowledge of the world is produced and thus the ways in which it can be governed.” (2015: 834)

“This article seeks to take the debate on Big Data in International Relations forward by foregrounding an analysis of Big Data’s epistemological claims and their ontological assumptions, rather than engaging with Big Data from already well-established critical positions, largely developed in the fields of politics and sociology.” (2015: 834)

“For many critical theorists, epistemological and ontological claims are secondary to concerns raised with regard to civil liberties, privacy, ownership and access issues,4 or when concerns with issues of knowledge production are raised they tend to quickly dismiss the claims of Big Data advocates on the basis that practical limits, regarding both the quantity and quality of the data available, mean that these claims cannot be met.” (2015: 834 – 835)

“Thus it suggests that the attractiveness of Big Data lies less in the serendipitous development of technological possibilities than in the growing dominance of posthumanist trends in social science; trends that are increasingly influential in the policy and practice of International Relations.” (2015: 835)

“…it suggests that the rise of posthumanist ontologies, reified in discussions of Big Data as a technique of knowledge production and of governance, profoundly constrain the possibilities for politics: reducing governance to an ongoing and technical process of adaptation, accepting the world as it is.” (2015: 835)

  • Big Data is characterised as “…the 3 ‘Vs’ which characterise it: volume, velocity and variety. Big Data includes information from a multitude of sources, including social media, smart phones and mapping, visualising and recording equipment7 and the number of data-sharing devices is growing exponentially.” (2015: 835)

“The term ‘Big Data’ is capitalised to distinguish it (as a set of ideas and practices discursively cohered around a certain approach to knowledge production) from its use as a merely descriptive term for a large amount of data.” (2015: 836)

“Thus Big Data discursively refers to a qualitative shift in the meaning of data, in not just the amount of data (approaching exhaustiveness) but also its quality (approaching a dynamic, fine-grained relational richness).” (2015: 836)

“Thus, Big Data transforms our everyday reality and our immediate relation to the things around us. This ‘datafication’ of everyday life is at the heart of Big Data: a way of accessing reality through bringing interactions and relationships to the surface and making them visible, readable and thereby governable, rather than seeking to understand hidden laws of causality.” (2015: 836)

“Big Data is thereby generally understood to generate a different type of ‘knowledge’: more akin to the translation or interpretation of signs rather than that of understanding chains of causation.” (2015: 836)

“Thus Big Data appears to lack certain attributes of the modernist ‘production process’ of knowledge and appears as less mediated through conceptual apparatuses.” (2015: 836-837)

“Big Data is the mirror image, methodologically, of other large data gathering exercises, such as national censuses based upon 30 or 40 questions, designed to elicit comparative and analytical data for policy-making. Big Data is understood to be generated from complex life or reality itself in the data trails left from our digital footprints as we go about our everyday lives.” (2015: 837)

“The analysis comes after the data is collected and stored, not prior to this. However, the fact that the data is not consciously generated, through the desire to test theories of models, is seen as an asset rather than a problem: ‘Big Data analytics enables an entirely new epistemological approach for making sense of the world; rather than testing a theory by analysing relevant data, new data analytics seek to gain insights “born from the data”’.” (2015: 837)

“Rather than starting with the human and then going out to the world, the promise of Big Data is that the human comes into the picture relatively late in the process (if at all).” (2016:837)

“Instead of beginning deductively with an hypothesis or theory, which is then tested through experimentation and modelling, Big Data seeks to be more inductive and thereby to preserve more of the ‘reality’ left out by abstract and sometimes reductionist causal assumptions.” (2015: 838)

“The possibility of data-intensive knowledge production informing policy developments has been broadly welcomed in International Relations, especially in the fields of disaster risk reduction, peacebuilding and resilience.” (2015: 838)

“The article then considers the affinities that these assumptions share with critical and posthuman understandings, suggesting that the rise of Big Data can be understood as enabling posthumanism to come of age: to inform new ways of governing in the world based upon process-based understandings and relational ontologies.” (2015:838)

“The discourse of Big Data seems to be inexorably drawn to reproducing its own methodological dynamic, data which cannot be used to govern from above, ‘serendipitously’ becomes a mechanism to enable governance ‘from below’.” (2015: 839)

“Not surprisingly, the rise of Big Data as a real-life policy solution (away from the commercial hype of deterministic predictions and total knowledge) is intimately linked not with the increase in governing responsibilities, based on centralised digital technologies of knowledge production and use, but the opposite: the conceived need to enable communities to govern themselves.” (2015:839)

“Big Data thus emerges not as a tool of international interveners equipped with predictive knowledge and able to redirect paths to development and peace but rather as a tool of local communities and ‘civil societies’, expected to generate their own knowledge of themselves and to act upon it accordingly.” (2015: 839)

“The unmediated and contextspecific nature of Big Data enable it to enable local communities to be proactive in their own governance, for example, in the ability to measure energy consumption, even located down to the energy consumption (from multiple sources of consumption) of individuals and households, or in the local measurement of environmental attributes such as pollution, river levels and land use changes. Big Data is thus held to enable empowerment in new ways at the most micro levels due to the digitalisation or ‘datafication’ of life.” (2015: 839-840)

“Rather than centralising data produced through everyday interactions and applying algorithms that produce linear and reductive understandings, the aspiration of Big Data is that multiple data sources can enable individuals, households and societies to practice responsive and reflexive self-management in ways which were considered impossible before.” (2015: 840)

“Big Data is alleged to help knowledge enable the people themselves rather than for them to provide knowledge to others. Thus Big Data can potentially empower precisely those that are most marginal and vulnerable at the moments of highest risk. Open information flows contribute to the building of resilience by making communities aware of the risks and hazards they may encounter so that they can mobilise to protect themselves.” (2015: 840)

“Thus, it is increasingly argued that Big Data should not merely be used by communities in response to disasters but could play a more preventive role. However, the preventive role of Big Data should not be confused with the linear predictions of reductionist models based on cause-and-effect theorising. It is this lack of theory that enables Big Data to be context dependent on local knowledge and correlations or factual information generated in real-time.” (2015: 840)

“In these instances, Big Data goes from being an accidental by-product of digitalised exchanges and becomes a technique of governing through the inculcation of self-knowledge.” (2015: 840-841)

“As Evgeny Morozov argues, Big Data approaches aspire to remove the need for governance on the basis of rules and laws, displacing this with real-time feedback mechanisms based on new forms of (datafied) self-awareness…” (2015: 841)

“It is important to note that in this perspective of Big Data as empowerment, the ‘power’ which Big Data promises local communities, in terms of capacity-building, relational awareness and resilience, is not the same type of power which governments claimed for themselves in the modernist era of linear cause-and-effect understandings.” (2015: 841)

“The ‘gift’ of Big Data does not seem to be very empowering for those who most need social change. Big Data can assist with the management of what exists, for example, redesigning transport or energy networks to meet peak demands or adapt to system breakdowns but it cannot provide more than technical assistance based upon knowing more about what exists in the here and now. The problem is that without causal assumptions it is not possible to formulate effective strategies and responses to problems of social, economic and environmental threats. Big Data does not empower people to change their circumstances but merely to be more aware of them in order to adapt to them.” (2015: 841 – 842).

“…the role of Big Data is not that of understanding and predicting disasters so as to prevent them but to enable communities to cope with them, through a better understanding of themselves. This process of inner-orientated knowledge replacing externally-orientated knowledge is captured well by Patrick Meier…” (2015: 842)

“Big Data aims not at instrumental or causal knowledge but at the revealing of feedback loops in real-time, enabling unintended consequences to be better and more reflexively managed.Disaster risk reduction thus becomes a way of making communities more selfaware so that the unintended consequences of social interaction do not undermine coping capacities. ” (2015: 843)

“Thus, It would be more useful to see Big Data as reflexive knowledge rather than as causal knowledge. Big Data cannot help explain global warming but it can enable individuals and household to measure their own energy consumption through the datafication of household objects and complex production and supply chains. Big Data thereby datafies or materialises an individual or community’s being in the world. This reflexive approach works to construct a pluralised and multiple world of self-organising and adaptive processes.” (2015: 843)

“Rather than engaging in external understandings of causality in the world, Big Data works on changing social behaviour by enabling greater adaptive reflexivity. If, through Big Data, we could detect and manage our own biorhythms and know the effects of poor eating or a lack of exercise, we could monitor our own health and not need costly medical interventions. Equally, if vulnerable and marginal communities could ‘datafy’ their own modes of being and relationships to their environments they would be able to augment their coping capacities and resilience without disasters or crises occurring.” (2015: 843)

“The increasing focus on cities that understand themselves and thereby govern themselves is driven by the technological possibilities of Big Data, where cities are understood as industrial and social hubs of complex interconnections, which through datafication can produce realtime knowledge of themselves. This reflexive awareness of cities’ own ‘vitality’ – their own ‘pulse’ – then enables a second order of reflexivity or of artificial intelligent ‘life’…” (2015: 844)

“The governance of the self, seemingly involves a different form of knowledge production and different forms of governance. This shift in understandings of knowledge, governance, power and agency is often captured in discussions of the posthuman.” (2015:844)

“The view of Big Data as empowering and capacity-building relies upon the reconstruction of societies as self-governing, as self-reproducing or autopoietic. However, this approach to self-government appears to be very different to modernist approaches of top-down governance, based on cause-and-effect understandings of policy interventions.” (2015: 844)

“It is therefore quite important to understand how this process works and how it is reflected in increasingly influential intellectual understandings. Data enables our embedded relationalities to become knowable. The more our interrelations become datafied and become transparent and readable the more we can understand the chains of contingent, complex and emergent causality which previously were invisible. The visibility of the complex world removes the need for causal theory and for top-down forms of governance on the basis of cause-and-effect. The self-awareness of a datafied world thereby blurs forever the distinction between human and nonhuman and subject and object. Big Data thereby articulates a properly posthuman ontology of self-governing, autopoietic assemblages of the technological and the social. Whereas the ‘human’ of modernist construction sought to govern through unravelling the mysteries of causation, the posthuman of our present world seeks to govern through enabling the relational reality of the world to become transparent, thus eliminating unintended consequences.” (2015:845)

***Pick up from page 845 ***

Egor Tsvetkov – YOUR FACE IS BIG DATA:

Egor Tsvetkov is a Rodchenko Art School Student and Russian Photographer. In 2016, he created a project that was aimed to create awareness to the pervasiveness of technology alongside the imminent lack of privacy that is associated with increased technological integration. Tsvetkov started by photographing about 100 people that sat across from him on the subway, he then used a proprietary facial-recognition app called: ‘FindFace’. The application then ‘taps neural-network technology’ and then tracks them down on Russian social media site ‘VK’ (PC World, 2016).

Unsurprisingly, Egor Tsvetkov found around 60-70% of his subjects with ease, those aged 18-35 were easiest to find whereas those who were older were more problematic (although this could be down to a lack of social networking use or even aged characteristics).

The photographer states that during the process, he was able to discover lots of information about the lives of these strangers. “Acting “like a Web stalker” was “uncomfortable for me,” Tsvetkov said via email”, “Then again, “my point in this art project is to show how technology breaks down the possibility of private life,” he said,. “It shows us the future”…”(PC World, 2016).

“Nowadays the power structures begin to lose their monopoly control over the ability to identify a person’s face and identify him with the help of photos and videos. But people are accustomed to differentiate patterns of behaviour in society and social networks, and leave the ability to spy on their best, successful moments of their lives for strangers. Such digital narcissim – a product of a culture of free expression that defines the new boundaries of private and public.

Intentional failure of using privacy settings has created a network stalking. Using free-for-all software, I was looking for the people who sat in front of me on the train underground. I learned about the life of people without any contact with them through the photos on the social network by comparing a real image with a web representation. The ability of quickly and anonymous serching people in network helps trace not for impersonal subject and within seconds concerts to a friend incognito.”  (Tsvetkov, E. 2018)

 

(BBC NEWS, 2018)

Trevor Paglen is a contemporary photographer that successfully created a critique of surveillance culture. He created a project through the acquisition of ‘spying and bulk data’ that has been collected by governmental bodies, by recreating this data physically, in the form of “landscape portraits of the US Intelligence buildings and the various infrastructures that are used to conduct their mass surveillance programs”. Paglen’s use of documentary style and abstract photography creates an in-depth analysis of cultural issues around freedom, big data, online anonymity, and the durations individuals spent online. “Paglen tells The Creators Project. “The internet, for example, is a thing that we think about in a very mystifying way. It’s this thing that nobody can quite describe that seems like its nowhere but everywhere at the same time.” (Chapman, 2018).

One of Trevor Paglen’s most notorious data-based project is titled “Trevor Paglen’s Deep Web Drive”, whereby he visited Florida beaches and coastlines underwater and examined “the internet cabled that channel an immeasurable flow of data and online traffic” (Chapman, 2018). These cables are utilised by “the National Security Agency to monitor and store digital information”, capturing absolutely everything from “selfies to Skype sessions”.

As our lives continuously and increasingly begin to spill out onto databases, we are all creating digital trails that are comprised from anything from internet searches, image posts or even simple ‘likes’ and ‘shares’. Increasingly, human life is becoming quantified, examined and stored for later referral.

“Today, the digitization of imagery breaks into both the conceptual and impressionistic areas of fine art, where experimentation is even more pronounced, and nonconcrete subjects such as the ‘digital sphere’ can be explored, and visualised using the photographic medium.” (Chapman, 2018)

Paglen states that we consider “images within the domain of culture where they’re open to interpretation” however due to the prolific use of the internet, “images are turned into data and producing data within the world”. Images are no longer recognised as a by-product of light and imaging processes but rather now are filled with additional layers of meta-data, geographical and temporal information. However, now, an image’s live only begins on the internet, as now it is shared over and over, assigned multiple meanings and contexts, and is assigned various tags, and keywords through social networking and hashtags.

“Paglen believes this is an indication of contemporary images have taken on a larger role, becoming active participants in the world, rather than a mere representation of it.” [E.g. Surveillance or traffic enforcement cameras] “That image will issues a ticket to the driver automatically”, he says. “That’s the kind of thing that I mean. The image is actually doing something between you and the traffic ticket.” “This sort of digital processing, indicative of mass surveillance and tracking techniques, is where visualisation and Paglen’s style of photographic documentation becomes important: using art to educate, advocate and explain the almost philosophical concepts of the online space.” (Champman, 2018)

Trevor Paglen – Trinity Cube (2015)

Trevor Paglen – Autonomy Cube

Trevor Paglen – Code Names

Paolo Cirlo – Street Ghosts

Paolo Cirlo created a project that is born from the data collected from Google Street View, these images were then posted and exhibited at the same physical locations in which they were extracted from via Google Street View. The images taken from Street View were printed at life-size scale and proportion and then returned to the original space in which they were captured. This scale and proportions used in printing these images have worked well to create a sense of realism whilst also working to highlight and add another layer to the digital and physical space by directly making visible the metadata attached to a certain space or time.

It is interesting to mention that there are various layers of construction and creation that take place here. Cirio has firstly discovered these images at specific sites and locations via Google Street View, he has then extracted these images and then he has isolated the subjects from their context or location by solely outlining the figures rather than extracting the whole composition. These extracted figures have then been taken and exhibited in a gallery space and lastly, these outlined and isolated figures are then placed in the original space in which they were first identified, as a means in which to raise awareness to contemporary issues. It is interesting to mention that the identities of these individuals have not been obscured by the artist but have simply been extracted via Google Street View which workes to raise awareness to the pervasive accessibility and availability to the public; these images are available to see to anyone who has an internet connection. The artist has both extracted the original subject and has been replaced in its original space and location. This is a multi-layered project that successfully investigates issues around data availability, mass surveillance and privacy issues in an interesting and highly understandable way.

Hasan Elahi – Tracking Transience

Hasan Elahi is a contemporary artist that critically examines contemporary issues such as “surveillance, citizenship, migration, transport, and the challenge of borders and frontiers.” (Elahi, 2018). His works have been featured in various prestigious exhibition venues such as the Sundance Film Festival and Venice Blennale. His works have frequently been picked up by Journalistic platforms such as ‘The New York Times”, “Forbes” and “Wired”. Elahi’s work addresses a wide and varying demographics, working alongside Tate Modern, TED and  The American Association of Artifical Intelligence to name a few. One of his most ambitious projects, titled “Tracking Transience”; is described as “… a self-tracking system that constantly and publically presents his exact location, activities, and other personal data. This self-surveillance project is a critique on contemporary investigative techniques and provides an ongoing “albi” for Elahi in the event of future accusations.” .

Fujitsu | Digital Co-Creation.

References:

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